Uncertainty Quantification in Water Resource Systems Modeling: Case Studies from India

Regional water resource modelling is important for evaluating system performance by analyzing the reliability, resilience and vulnerability criteria of the system. In water resource systems modelling, several uncertainties abound, including data inadequacy and errors, modeling inaccuracy, lack of knowledge, imprecision, inexactness, randomness of natural phenomena, and operational variability, in addition to challenges such as growing population, increasing water demands, diminishing water sources and climate change. Recent advances in modelling techniques along with high computational capabilities have facilitated rapid progress in this area. In India, several studies have been carried out to understand and quantify uncertainties in various basins, enumerate large temporal and regional mismatches between water availability and demands, and project likely changes due to warming. A comprehensive review of uncertainties in water resource modelling from an Indian perspective is yet to be done. In this work, we aim to appraise the quantification of uncertainties in systems modelling in India and discuss various water resource management and operation models. Basic formulation of models for probabilistic, fuzzy and grey/inexact simulation, optimization, and multi-objective analyses to water resource design, planning and operations are presented. We further discuss challenges in modelling uncertainties, missing links in integrated systems approach, along with directions for future.

[1]  Subimal Ghosh,et al.  Statistical downscaling of GCM simulations to streamflow using relevance vector machine , 2008 .

[2]  F. Giorgi,et al.  Calculation of average, uncertainty range, and reliability of regional climate changes from AOGCM simulations via the reliability ensemble averaging (REA) method , 2002 .

[3]  Ajay Kumar Bhurjee,et al.  Interval-valued facility location model: An appraisal of municipal solid waste management system , 2018 .

[4]  Daniel P. Loucks,et al.  Managing Water as a Critical Component of a Changing World , 2017, Water Resources Management.

[5]  C. Dhanya,et al.  Modeling of extreme risk in river water quality under climate change , 2018 .

[6]  P. P. Mujumdar,et al.  A Bayesian Stochastic Optimization Model for a Multi-Reservoir Hydropower System , 2007 .

[7]  Reservoir Operations under Changing Climate Conditions: Hydropower-Production Perspective , 2019, Journal of Water Resources Planning and Management.

[8]  Zaher Mundher Yaseen,et al.  A survey on river water quality modelling using artificial intelligence models: 2000–2020 , 2020 .

[9]  Santosh M. Avvannavar,et al.  Evaluation of water quality index for drinking purposes for river Netravathi, Mangalore, South India , 2008, Environmental monitoring and assessment.

[10]  Ajay Kumar Bhurjee,et al.  A facility location model for municipal solid waste management system under uncertain environment. , 2017, The Science of the total environment.

[11]  P. P. Mujumdar,et al.  A fuzzy risk approach for seasonal water quality management of a river system , 2002 .

[12]  Shi-Mei Choong,et al.  State-of-the-Art for Modelling Reservoir Inflows and Management Optimization , 2015, Water Resources Management.

[13]  Stefano Galelli,et al.  On the representation of water reservoir storage and operations in large-scale hydrological models: implications on model parameterization and climate change impact assessments , 2019 .

[14]  Sangeeta Kumari,et al.  Reservoir Operation with Fuzzy State Variables for Irrigation of Multiple Crops , 2015 .

[15]  Abbas Afshar,et al.  State of the Art Review of Ant Colony Optimization Applications in Water Resource Management , 2015, Water Resources Management.

[16]  D. G. Regulwar,et al.  Multipurpose Reservoir Operating Policies: A Fully Fuzzy Linear Programming Approach , 2013 .

[17]  J. Patz,et al.  Climate change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers. , 2007 .

[18]  D. Rosenberg Shades of grey: A critical review of grey-number optimization , 2009 .

[19]  Md. Shabbir Hossain,et al.  Intelligent Systems in Optimizing Reservoir Operation Policy: A Review , 2013, Water Resources Management.

[20]  V. Jothiprakash,et al.  A multiobjective fuzzy linear programming model for sustainable integrated operation of a multireservoir system , 2016 .

[21]  Guohe Huang,et al.  A fuzzy-Markov-chain-based analysis method for reservoir operation , 2012, Stochastic Environmental Research and Risk Assessment.

[22]  Jan Seibert,et al.  Evaluation of different downscaling techniques for hydrological climate-change impact studies at the catchment scale , 2011 .

[23]  Avi Ostfeld,et al.  The future of water resources systems analysis: Toward a scientific framework for sustainable water management , 2015 .

[24]  Ajit Pratap Singh,et al.  Water quality management of a stretch of river Yamuna: An interactive fuzzy multi-objective approach , 2007 .

[25]  P P Mujumdar,et al.  An imprecise fuzzy risk approach for water quality management of a river system. , 2009, Journal of environmental management.

[26]  Millie Pant,et al.  Dynamic programming integrated particle swarm optimization algorithm for reservoir operation , 2020, Int. J. Syst. Assur. Eng. Manag..

[27]  P. Mujumdar,et al.  Constraining uncertainty in regional hydrologic impacts of climate change: Nonstationarity in downscaling , 2010 .

[28]  John W. Labadie,et al.  Multiobjective Watershed-Level Planning of Storm-Water Detention Systems , 1997 .

[29]  P. P. Mujumdar,et al.  Performance evaluation of an irrigation system under some optimal operating policies , 1992 .

[30]  P. Mujumdar,et al.  Reservoir performance under uncertainty in hydrologic impacts of climate change , 2010 .

[31]  W. R. Lynn,et al.  Probabilistic models for predicting stream quality , 1966 .

[32]  Guohe Huang,et al.  Analysis of Solution Methods for Interval Linear Programming , 2011 .

[33]  N. V. Umamahesh,et al.  Optimal Irrigation Planning under Water Scarcity , 2006 .

[34]  S. Simonovic,et al.  Integrated Reservoir Management System for Adaptation to Climate Change: The Nakdong River Basin in Korea , 2010 .

[35]  Junye Wang,et al.  Water Quality Management of a Cold Climate Region Watershed in Changing Climate , 2019, Journal of Environmental Informatics.

[36]  Nahum Gershon,et al.  Modeling Complex Data for Creating Information , 2011 .

[37]  Cengiz Kahraman,et al.  Fuzzy Multi-Criteria Decision Making: Theory and Applications with Recent Developments , 2008 .

[38]  Slobodan P. Simonovic,et al.  Fuzzy multiobjective models for optimal operation of a hydropower system , 2013 .

[39]  Subimal Ghosh,et al.  Modeling GCM and scenario uncertainty using a possibilistic approach: Application to the Mahanadi River, India , 2008 .

[40]  V. Jothiprakash,et al.  Comparison of Policies Derived from Stochastic Dynamic Programming and Genetic Algorithm Models , 2009 .

[41]  Shashidhar Thatikonda,et al.  Fuzzy-Based Regional Water Quality Index for Surface Water Quality Assessment , 2019, Journal of Hazardous, Toxic, and Radioactive Waste.

[42]  Barbara J. Lence,et al.  Markov Chain Model for Seasonal-Water Quality Management , 1995 .

[43]  R. Zamani-Ahmadmahmoodi,et al.  Water quality evaluation using water quality index and multivariate methods, Beheshtabad River, Iran , 2018, Applied Water Science.

[44]  K. Venugopal,et al.  Optimal Operation of South Indian Irrigation Systems , 1998 .

[45]  P. P. Mujumdar,et al.  Grey fuzzy optimization model for water quality management of a river system , 2006 .

[46]  R. Leconte,et al.  Uncertainty of the impact of climate change on the hydrology of a nordic watershed , 2008 .

[47]  Deepti Rani,et al.  Simulation–Optimization Modeling: A Survey and Potential Application in Reservoir Systems Operation , 2010 .

[48]  P. Mujumdar,et al.  Climate change induced risk in water quality control problems , 2012 .

[49]  Hubert H. G. Savenije,et al.  Integrated water resources management: Concepts and issues , 2008 .

[50]  P. P. Mujumdar,et al.  Risk minimization in water quality control problems of a river system , 2006 .

[51]  Slobodan P. Simonovic,et al.  Inverse flood risk modelling under changing climatic conditions , 2007 .

[52]  S. Vedula,et al.  An Integrated Model for Optimal Reservoir Operation for Irrigation of Multiple Crops , 1996 .

[53]  Slobodan P. Simonovic,et al.  Reservoir Systems Analysis: Closing Gap between Theory and Practice , 1992 .

[54]  P. P. Mujumdar,et al.  Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties , 2014, Water Resources Management.

[55]  S. Simonovic,et al.  Are we modelling impacts of climatic change properly? , 2006 .

[56]  Omid Bozorg-Haddad,et al.  State-of-art of genetic programming applications in water-resources systems analysis , 2020, Environmental Monitoring and Assessment.

[57]  Ahmed El-Shafie,et al.  Reservoir Optimization in Water Resources: a Review , 2014, Water Resources Management.

[58]  S. Chapra Surface Water-Quality Modeling , 1996 .

[59]  Ni-Bin Chang,et al.  Sustainable Solid Waste Management: A Systems Engineering Approach , 2015 .

[60]  Mike Hulme,et al.  Representing uncertainty in climate change scenarios: a Monte-Carlo approach , 2000 .

[61]  Vijay K. Minocha,et al.  Fuzzy optimization model for water quality management of a river system - Closure , 1999 .

[62]  Lucien Duckstein,et al.  Fuzzy Rule-Based Modeling of Reservoir Operation , 1996 .

[63]  G. Huang,et al.  Grey integer programming: An application to waste management planning under uncertainty , 1995 .

[64]  K. Srinivasa Raju,et al.  Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming , 2010 .

[65]  Sabah S. Fayaed,et al.  Reservoir-system simulation and optimization techniques , 2013, Stochastic Environmental Research and Risk Assessment.

[66]  Sangeeta Kumari,et al.  Fuzzy Set–Based System Performance Evaluation of an Irrigation Reservoir System , 2017 .

[67]  N. V. Umamahesh,et al.  Technical Communication: Two-Phase Stochastic Dynamic Programming Model for Optimal Operation of Irrigation Reservoir , 1997 .

[68]  Alex S. Mayer,et al.  Integrated Water Resources Optimization Models: An Assessment of a Multidisciplinary Tool for Sustainable Water Resources Management Strategies , 2009 .

[69]  Sebastian Vicuna,et al.  Basin‐scale water system operations with uncertain future climate conditions: Methodology and case studies , 2010 .

[70]  S. Vedula,et al.  Water resources systems:modelling techniques and analysis , 2015 .

[71]  P. P. Mujumdar,et al.  Optimal reservoir operation for irrigation of multiple crops , 1992 .

[72]  Adebayo Adeloye,et al.  Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations , 2015, Water Resources Management.

[73]  Sangamreddi Chandramouli,et al.  Comparison of stochastic and fuzzy dynamic programming models for the operation of a multipurpose reservoir , 2011 .

[74]  Ajit Pratap Singh,et al.  Managing water quality of a river using an integrated geographically weighted regression technique with fuzzy decision-making model , 2019, Environmental Monitoring and Assessment.

[75]  Daniel P. Loucks,et al.  Water management: Current and future challenges and research directions , 2015 .

[76]  Sanjay Mehrotra,et al.  Stochastic Robust Mathematical Programming Model for Power System Optimization , 2016, IEEE Transactions on Power Systems.

[77]  Dushmanta Dutta,et al.  Analysis of water resources in the Mahanadi River Basin, India under projected climate conditions , 2008 .

[78]  D. G. Regulwar,et al.  Development of 3-D Optimal Surface for Operation Policies of a Multireservoir in Fuzzy Environment Using Genetic Algorithm for River Basin Development and Management , 2008 .

[79]  Slobodan P. Simonovic,et al.  A spatial multi-objective decision-making under uncertainty for water resources management , 2005 .

[80]  H. Loáiciga,et al.  Application of non-animal–inspired evolutionary algorithms to reservoir operation: an overview , 2019, Environmental Monitoring and Assessment.

[81]  Subhankar Karmakar,et al.  GREY FUZZY MULTI-OBJECTIVE OPTIMIZATION , 2008 .

[82]  Paulin Coulibaly,et al.  Uncertainty analysis of statistical downscaling methods , 2006 .

[83]  Laurence Tianruo Yang,et al.  Fuzzy Logic with Engineering Applications , 1999 .

[84]  S. Beguería,et al.  Long-term sustainability of large water resource systems under climate change: A cascade modeling approach , 2020 .

[85]  M. Rosegrant,et al.  Modeling water resources management at the basin level: review and future directions , 2018 .

[86]  P. P. Mujumdar,et al.  Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster–Shafer and Bayesian approaches , 2010 .

[87]  P. Mujumdar,et al.  Fuzzy State Real-Time Reservoir Operation Model for Irrigation with Gridded Rainfall Forecasts , 2016 .

[88]  H. Fowler,et al.  Modeling the impacts of future climate change on water resources for the Gállego river basin (Spain) , 2012 .

[89]  S. Simonovic,et al.  System Dynamics Approach for Assessing the Behaviour of the Lim Reservoir System (Serbia) under Changing Climate Conditions , 2019, Water.

[90]  Samuel O. Russell,et al.  Reservoir Operating Rules with Fuzzy Programming , 1996 .

[91]  V. Jothiprakash,et al.  Efficient discretization of state variables in stochastic dynamic programming model of Ukai reservoir, India , 2016 .

[92]  P. P. Mujumdar,et al.  Reservoir Operation Modelling with Fuzzy Logic , 2000 .

[93]  Seyed Jamshid Mousavi,et al.  A stochastic dynamic programming model with fuzzy storage states for reservoir operations , 2004 .